Tracking picosecond strain pulses in heterostructures that exhibit giant magnetostriction.

We combine ultrafast X-ray diffraction (UXRD) and time-resolved Magneto-Optical Kerr Effect (MOKE) measurements to monitor the strain pulses in laser-excited TbFe2/Nb heterostructures. Spatial separation of the Nb detection layer from the laser excitation region allows for a background-free characterization of the laser-generated strain pulses. We clearly observe symmetric bipolar strain pulses if the excited TbFe2 surface terminates the sample and a decomposition of the strain wavepacket into an asymmetric bipolar and a unipolar pulse, if a SiO2 glass capping layer covers the excited TbFe2 layer. The inverse magnetostriction of the temporally separated unipolar strain pulses in this sample leads to a MOKE signal that linearly depends on the strain pulse amplitude measured through UXRD. Linear chain model simulations accurately predict the timing and shape of UXRD and MOKE signals that are caused by the strain reflections from multiple interfaces in the heterostructure.

Intrinsic magnetic properties of bimetallic nanoparticles elaborated by cluster beam deposition.

In this paper, we present some specific chemical and magnetic order obtained very recently on characteristic bimetallic nanoalloys prepared by mass-selected Low Energy Cluster Beam Deposition (LECBD). We study how the competition between d-atom hybridization, complex structure, morphology and chemical affinity affects their intrinsic magnetic properties at the nanoscale. The structural and magnetic properties of these nanoalloys were investigated using various experimental techniques that include High Resolution Transmission Electron Microscopy (HRTEM), Superconducting Quantum Interference Device (SQUID) magnetometry, as well as synchrotron techniques such as Extended X-ray Absorption Fine Structure (EXAFS) and X-ray Magnetic Circular Dichroism (XMCD). Depending on the chemical nature of the nanoalloys we observe different magnetic responses compared to their bulk counterparts. In particular, we show how specific relaxation in nanoalloys impacts their magnetic anisotropy; and how finite size effects (size reduction) inversely enhance their magnetic moment.

Low temperature ferromagnetism in chemically ordered FeRh nanocrystals.

In sharp contrast to previous studies on FeRh bulk, thin films, and nanoparticles, we report the persistence of ferromagnetic order down to 3 K for size-selected 3.3 nm diameter nanocrystals embedded into an amorphous carbon matrix. The annealed nanoparticles have a B2 structure with alternating atomic Fe and Rh layers. X-ray magnetic dichroism and superconducting quantum interference device measurements demonstrate ferromagnetic alignment of the Fe and Rh magnetic moments of 3 and 1µ(B), respectively. The ferromagnetic order is ascribed to the finite-size induced structural relaxation observed in extended x-ray absorption spectroscopy.

Toward the border between neural and Markovian paradigms.

A new tendency in the design of modern signal processing methods is the creation of hybrid algorithms. This paper gives an overview of different signal processing algorithms situated halfway between Markovian and neural paradigms. A new systematic way to classify these algorithms is proposed. Four specific classes of models are described. The first one is made up of algorithms based upon either one of the two paradigms, but including some parts of the other one. The second class includes algorithms proposing a parallel or sequential cooperation of two independent Markovian and neural parts. The third class tends to show Markov models (MMs) as a special case of neural networks (NNs), or conversely NNs as a special case of MMs. These algorithms concentrate mainly on bringing together respective learning methods. The fourth class of algorithms are hybrids, neither purely Markovian nor neural. They can be seen as belonging to a more general class of models, presenting features from both paradigms. The first two classes essentially include models with structural modifications, while two later classes propose algorithmic modifications. For the sake of clarity, only main mathematical formulas are given. Specific applications are intentionally avoided to give a wider view of the subject. The references provide more details for interested readers.

Estimation of fuzzy Gaussian mixture and unsupervised statistical image segmentation.

This paper addresses the estimation of fuzzy Gaussian distribution mixture with applications to unsupervised statistical fuzzy image segmentation. In a general way, the fuzzy approach enriches the current statistical models by adding a fuzzy class, which has several interpretations in signal processing. One such interpretation in image segmentation is the simultaneous appearance of several thematic classes on the same site. We introduce a new procedure for estimating of fuzzy mixtures, which is an adaptation of the iterative conditional estimation (ICE) algorithm to the fuzzy framework, We first describe the blind estimation, i.e., without taking into account any spatial information, valid in any context of independent noisy observations. Then we introduce, in a manner analogous to classical hard segmentation, the spatial information by two different approaches: contextual segmentation and adaptive blind segmentation. In the first case, the spatial information is taken into account at the segmentation step level, and in the second case it is taken into account at the parameter estimation step level. The results obtained with the iterative conditional estimation algorithm are compared to those obtained with expectation-maximization (EM) and the stochastic EM algorithms, on both parameter estimation and unsupervised segmentation levels, via simulations. The methods proposed appear as complementary to the fuzzy C-means algorithms.

Immunogenicity and safety in newborns of a new recombinant hepatitis B vaccine containing the S and pre-S2 antigens.

A study to evaluate the safety and immunogenicity of a recombinant hepatitis B vaccine containing the S and pre-S2 antigens (GenHevac B Pasteur) was conducted in healthy newborn infants. All infants received 20 micrograms of vaccine within 24 h of birth and at 1 and 2 months with a booster injection at month 12. The vaccine was administered alone in 19 infants born to low risk mothers, i.e. surface antigen (HBsAg)-negative and antibody to the core antigen (Anti-HBc)-positive mothers. The vaccine was administered in combination with 100 IU hepatitis B immune globulin (HBIg) at birth and 1 month in 18 infants born to high risk mothers, i.e. HBsAg positive mothers. In the group not receiving HBIg, the anti-HBs seroconversion rate at the 10 mIU ml-1 threshold was 50% 1 month after the first injection. In both groups, the anti-HBs seroconversion rates were 100% 1 month after the third injection and greater than 85% 1 month after the second injection. After the booster injection greater than 90% of the infants had an anti-HBs titre greater than 1000 mIU ml-1 which will probably provide them with adequate protection for several years. The kinetics of the anti-pre-S2 response was similar to that of the anti-HBs response and 100% of infants in both groups had seroconverted 1 month after the second injection of the vaccine. The side effects were scarce, all mild and transient.(ABSTRACT TRUNCATED AT 250 WORDS)